The present invention relates generally to magnetic resonance (MR) imaging and, more particularly, to a method of image reconstruction using phase correction and Variable Readout Gradient Filtering (VRGF).
When a substance such as human tissue is subjected to a uniform magnetic field (polarizing field B0), the individual magnetic moments of the spins in the tissue attempt to align with this polarizing field, but precess about it in random order at their characteristic Larmor frequency. If the substance, or tissue, is subjected to a magnetic field (excitation field B1) which is in the x-y plane and which is near the Larmor frequency, the net aligned moment, or “longitudinal magnetization”, Mz, may be rotated, or “tipped”, into the x-y plane to produce a net transverse magnetic moment Mt. A signal is emitted by the excited spins after the excitation signal B1 is terminated and this signal may be received and processed to form an image.
When utilizing these signals to produce images, magnetic field gradients (Gx, Gy, and Gz) are employed. Typically, the region to be imaged is scanned by a sequence of measurement cycles in which these gradients vary according to the particular localization method being used. The resulting set of received NMR signals are digitized and processed to reconstruct the image using one of many well known reconstruction techniques.
Echo Planar Imaging (EPI) is used for many MR imaging applications, including Diffusion Weighted Imaging (DWI), Diffusion Tensor Imaging (DTI), and functional Magnetic Resonance Imaging (fMRI), because of its ability to rapidly acquire diagnostic images. Echo Planar Imaging relies upon bi-polar magnetic gradient fields to acquire MR data. More particularly, EPI is a rapid imaging technique that records an entire image in a repetition interval or TR period. An EPI pulse sequence is generally characterized by a 90° slice selective RF pulse that is applied in conjunction with a slice selection gradient. An initial phase encoding gradient pulse and an initial frequency encoding gradient pulse is used to position spins at a corner of k-space, the matrix that is used to define the relative position of acquired signals along a phase encoding and a frequency encoding direction. A 180° pulse is then applied. Typically, this 180° pulse is not slice selective. The phase and frequency encoding directions are then cycled using phase encoding and readout pulses so as to transverse k-space. In this regard, a frequency encoding gradient follows a phase encoding gradient to record a time signal. Another phase encoding gradient is then applied followed by a reverse polarity frequency gradient during which another time signal is recorded. This cycling continues until k-space is filled. Because k-space can be rapidly traversed in this fashion, images can be acquired at a rate tantamount to video rates, e.g. 15–30 images per second, or faster.
It is possible during EPI scanning to acquire frames of data in such a manner that acquisition occurs during transition regions (ramps) of readout gradients as well as during the steady-state (flat-top) regions of readout gradients. This data acquisition technique is known as ramp-sampling, since a portion of the data acquisition occurs on readout gradient ramps. Once MR data has been acquired using a variable readout gradient such as this, a re-sampling process is performed on the data acquired to create a rectilinear k-space grid representing uniformly sampled MR data points. This re-sampling process, typically performed during MR image reconstruction, is known as VRGF re-sampling. It is typically implemented as a discrete-time convolution with a unique convolution kernel for each output data point.
EPI has been successfully used for a number of clinical applications, and is particularly useful in studies involving the human brain. DWI and DTI are imaging sequences that can be used to obtain useful diagnostic information, e.g. localization of areas damaged by ischemia or hemorrhagic stroke, creation of anisotropic diffusion coefficient (ADC) maps, enhanced anisotropic diffusion coefficient (eADC) maps, and tractography images.
Another important EPI application is fMRI of the brain. Brain fMRI is an imaging technique that relates functional activity occurring in specific locations of the brain to various stimuli, such as speech, motor functions, or visual stimulus. With fMRI it is possible to measure momentary increases in blood flow to specific thought or motor control centers that occur in response to a stimulus. For example, in response to movement of the right index finger, a rapid momentary increase in blood circulation of the specific part of the brain controlling finger movement occurs. Such an increase in blood circulation also yields an increase in oxygen which is paramagnetic and thus affects spin-lattice and spin-spin relaxation times of local brain tissues. These differences in relaxation times manifest themselves as variations in image contrast and can then be exploited with EPI to measure brain function.
A drawback of EPI is that phase errors that lead to image artifacts when not removed from the raw data may be introduced during data acquisition. EPI sequences use a single RF pulse followed by multiple data acquisition windows to encode multiple frames of MR data per RF excitation. While this speeds the rate of data collection, EPI data contains phase errors that result in “Nyquist” ghosting in the phase encoding direction. For a single-shot EPI data collection, Nyquist ghosting manifests itself as an artifact resembling the original image shifted and split in the phase direction.
A number of processes have been developed to correct for these phase errors. Known processes are predicated upon the acquisition of non-phase-encoded reference data, determining phase errors in the reference data, and correcting phase-encoded data based on the phase errors present in the reference data. While these processes have been fruitful in reducing image artifacts due to phase errors in EPI, there still remains a need for further improvement in reducing image artifacts due to phase errors with EPI.
It would therefore be desirable to have a system and method capable of correcting phase errors in ramp-sampled EPI MR data to reduce image artifacts in reconstructed images.